Optimizing Forest Sampling by using Lagrange Multipliers

Suhud Wahyudi, Farida Agustini Widjajati, Dea Oktavianti


To obtain information from a population, we use a sampling method. One of sampling techniques that we can use is double sampling. Double sampling is a sampling technique based on the information of first phase which is used as an additional information obtaining estimates for the second phase. In this case, we discuss the model of double sampling with regression estimator. Then, to obtain the optimal number of samples for the first and second phases, we use Lagrange multipliers. The model analysis result is a formula to calculate the optimal number of samples for the first phase (n0) and the second phase (n1). Implementation of this method is simulated by using teak stands data from previous studies at Forest Management Unit (FMU) Madiun which consists of Section Forest Management Units (FSMU) Dagangan and Dungus. The calculation result of data from FSMU Dagangan, we get optimal number of plots must be observed in image interpretation are 149 plots and field survey are 14 plots. And with the data from FSMU Dungus, we get optimal number of plots to be observed in image interpretation are 153 plots and field survey are 20 plots.


Double sampling; Lagrange multiplier optimizations; regression estimator

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DOI: http://dx.doi.org/10.12962/j24775401.v3i2.2883


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International Journal of Computing Science and Applied Mathematics by Pusat Publikasi Ilmiah LPPM, Institut Teknologi Sepuluh Nopember is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at https://iptek.its.ac.id/index.php/ijcsam.